"We have 50 years of expertise walking around in people's heads. It's never been written down. It can't be searched. And every day, a little more of it disappears." — VP of Operations, Fortune 500 Manufacturer
What if you could capture, retain, and multiply that knowledge?
Every year, enterprises lose $3.1 trillion to knowledge that was never captured, expertise that isn't retained, and wisdom that can't scale.
- Knowledge never captured — Your best operators make split-second decisions based on decades of pattern recognition. None of it is written down.
- Knowledge not retained — Even when documented, context fades. The why behind decisions gets lost. Procedures exist but understanding doesn't.
- Knowledge not multiplied — One expert can only be in one place. Their judgment doesn't scale. New hires take years to develop the same instincts.
- Knowledge walking out the door — When veterans leave, retire, or move on, their expertise leaves with them.
Traditional solutions don't work:
- Documentation? Captures the what, loses the why. Outdated the moment it's written.
- Knowledge bases? Graveyards of stale wikis nobody searches.
- Knowledge graphs? Promising, but prohibitively expensive to build and maintain.
The brutal truth: In most enterprises, critical operating knowledge exists in exactly one place—people's heads. It was never captured. It's not being retained. And it certainly isn't multiplying.
Imagine an enterprise where:
-
A new engineer asks "Why do we heat-treat at 450°F instead of 500°F?" and gets the actual reasoning—traced back to the 2019 incident that taught everyone that lesson.
-
Your AI assistant doesn't just search documents—it understands how your processes connect, why decisions were made, and what happens downstream when something changes.
-
When regulations shift, you know instantly which procedures are affected, who owns them, and what needs to change.
-
Domain expertise isn't locked in veterans' heads—it's encoded, evolving, and available to every agent and every employee, 24/7.
This is the Cognitive Enterprise. And Dana makes it possible.
The secret is a new architectural layer: Cognitive Ontology—a living knowledge graph that captures not just what your enterprise knows, but how things connect and why decisions get made.
┌──────────────────────────────────────────────────────────────────────────┐
│ TODAY: KNOWLEDGE TRAPPED │
│ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ HUMAN OPERATORS │ │
│ │ (context lives only in their heads) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ DATA LAYER │ │
│ │ (databases, documents, logs — disconnected) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────────────────┘
┌──────────────────────────────────────────────────────────────────────────┐
│ TOMORROW: KNOWLEDGE LIBERATED │
│ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ HUMAN OPERATORS │ │
│ │ (amplified by encoded expertise) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ COSTAR AGENTS │ │
│ │ (continuously build and apply knowledge) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ COGNITIVE ONTOLOGY │ │
│ │ (living knowledge graph — built by agents, for agents) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ DATA LAYER │ │
│ │ (now connected, contextualized, alive) │ │
│ └──────────────────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────────────────┘
The key insight: Traditional knowledge graphs failed because humans had to build and maintain them. That's expensive and unsustainable.
Dana's breakthrough: Intelligent agents build the ontology automatically—extracting knowledge from documents, learning from experts, and evolving the graph continuously. The ontology is cognitive because it's created by cognition, for cognition.
Dana agents follow the COSTAR lifecycle—a continuous loop of knowledge building and application:
┌────────────────────────────────────────────────────────────────────────┐
│ │
│ COSTAR AGENT LIFECYCLE │
│ │
│ KNOWLEDGE AGENTS COGNITIVE TASK AGENTS │
│ (build the ontology) ONTOLOGY (use the ontology) │
│ │
│ ┌──────────┐ ┌───────────────┐ ┌──────────┐ │
│ │ CURATE │──────────▶│ │─────────▶│ SEE │ │
│ └──────────┘ extract │ Domain │ context └────┬─────┘ │
│ │ knowledge │ Knowledge │ │ │
│ ▼ │ Graph │ ▼ │
│ ┌──────────┐ │ │ ┌──────────┐ │
│ │ ORGANIZE │──────────▶│ ┌─────────┐ │ │ THINK │ │
│ └──────────┘ structure │ │ Entity │ │ └────┬─────┘ │
│ │ ├─────────┤ │ │ │
│ │ │ Entity │ │ ▼ │
│ ┌──────────┐ │ ├─────────┤ │ ┌──────────┐ │
│ │ REFLECT │◀──────────│ │ Entity │ │◀─────────│ ACT │ │
│ └──────────┘ learning │ └─────────┘ │ results └────┬─────┘ │
│ ▲ │ Causal Links │ │ │
│ │ └───────────────┘ ▼ │
│ │ ▲ ┌──────────┐ │
│ │ └───────────────────│ REFLECT │ │
│ │ feedback └────┬─────┘ │
│ └─────────────────────────────────────────────────┘ │
│ │
└────────────────────────────────────────────────────────────────────────┘
| Phase | What Happens | The Outcome |
|---|---|---|
| Curate | Extract knowledge from documents, experts, operations | Expertise that lived in heads becomes accessible |
| Organize | Structure into causal and contextual relationships | Agents understand why, not just what |
| See | Perceive situations through accumulated expertise | Anomalies detected that humans would miss |
| Think | Reason with domain knowledge, not just patterns | Diagnoses in minutes, not days |
| Act | Execute with encoded institutional judgment | Decisions made at 3 AM without waiting for experts |
| Reflect | Learn from outcomes, improve the ontology | Every action makes the system smarter |
The result: Agents that don't just follow instructions—they understand your domain.
The ontology enables reasoning. Reasoning enables action. Here's what becomes possible when agents truly understand your domain:
| Before Dana | With Dana Agents |
|---|---|
| Alert fires → human investigates → human diagnoses → human decides → human acts | Agent perceives, diagnoses, decides, and acts—pages human only when needed |
| Expert reviews 200 cases/day with tribal knowledge | Agent processes 5,000 cases/day with encoded expert judgment |
| New hire shadows veterans for 6 months | New hire works alongside an agent that has the veteran's knowledge |
| 3 AM anomaly waits until morning shift | 3 AM anomaly resolved at 3:04 AM |
| "Why did we reject this batch?" → 3-day investigation | "Why did we reject this batch?" → instant causal trace with evidence |
| Regulatory change → months of manual procedure review | Regulatory change → instant impact analysis, draft remediation |
The shift: From humans doing cognitive labor while AI assists → to agents doing cognitive labor while humans supervise.
This is not about answering questions. It's about doing the work that previously required scarce human expertise—continuously, at scale, at 3 AM.
"Dana agents autonomously reclassify 2,400 wafer defects per shift with 94% accuracy—work that consumed 3 FTEs of tedious expert review. Root-cause analysis that took senior engineers 3 days now happens in 20 minutes, automatically, at 3 AM."
"Our compliance agent reviewed 14,000 loan files in 6 hours, flagging 847 exceptions with full audit trails. Previously: 4 analysts, 3 weeks, and we still missed things. The agent doesn't just find problems—it explains them in regulatory language and drafts the remediation."
"When a heat exchanger drifted out of spec at 2 AM, the Dana agent diagnosed failing tube fouling (not pump failure—the obvious guess), adjusted flow rates to compensate, scheduled maintenance for the optimal window, and briefed the morning shift. No human touched it. No production lost."
pip install dana
dana studiofrom adana.core.agent import STARAgent
# Create an agent grounded in your domain knowledge
agent = STARAgent(agent_type="operations_expert")
# Point it at your knowledge sources
agent.with_resources(
rag_resource("./procedures"),
rag_resource("./incident_reports"),
rag_resource("./equipment_manuals")
)
# The agent monitors, reasons, and acts autonomously
agent.on_event("sensor_anomaly", handler=lambda e: agent.diagnose_and_respond(e))
# When furnace #3 shows temperature drift at 2:47 AM:
# → Agent correlates with similar patterns from 2019 incident IR-2019-0847
# → Identifies root cause: failing thermocouple (not heater element)
# → Initiates controlled cooldown per SOP-HT-003 emergency procedures
# → Pages on-call engineer with diagnosis and recommended action
# → Logs decision rationale for continuous learning
# Result: Problem contained in 4 minutes. Previously took 2+ hours
# of expert diagnosis—if someone was awake to notice.Every enterprise will become a Cognitive Enterprise. The only question is when—and whether you'll lead or follow.
The companies deploying cognitive agents today will:
- Automate expert judgment—not just routine tasks, but decisions that previously required veterans
- Operate continuously—agents that diagnose, decide, and act at 3 AM without waiting for morning
- Scale expertise infinitely—one expert's knowledge, encoded, serving thousands of decisions per hour
- Compound institutional intelligence—every action teaches the system, making tomorrow's agents smarter than today's
Dana makes this accessible now. Not in some distant future. Not requiring massive infrastructure investments. Today.
dana/
├── dana_lang/ # Language runtime & COSTAR frameworks
├── dana_agent/ # COSTAR agent implementation
├── dana_studio/ # Visual agent builder
├── dana/ # Contrib modules
├── examples/ # Ready-to-run examples
├── tests/ # Test suites
├── docs/ # Documentation
└── bin/ # CLI tools & scripts
- Quick Start Guide — Running in 5 minutes
- Core Concepts — Understanding COSTAR and Cognitive Ontology
- Enterprise Deployment — Scaling to production
- GitHub Issues — Report bugs, request features
- Discord — Join the community
Building something mission-critical? Talk to us.
Dana: Where Enterprise Knowledge Becomes Immortal
© 2025 Aitomatic, Inc. · MIT License